Miłosz Kadziński
- Management Science and Operations Research top 0.2%
- Artificial Intelligence top 1%
- Computational Theory and Mathematics top 0.5%
- Control and Systems Engineering top 2%
- Statistics and Probability top 1%
- Co-authors
- Roman SłowińskiSalvatore GrecoTommi TervonenKannan GovindanMarco CinelliR. SivakumarSalvatore CorrenteMichael A. Gonzalez
- Topics
- Multi-Criteria Decision Making (59 papers)Rough Sets and Fuzzy Logic (19 papers)Advanced Multi-Objective Optimization Algorithms (17 papers)
- Cited by
- Management Science and Operations ResearchStatistics and ProbabilityComputational Theory and Mathematics
- Journals
- Journal of Cleaner ProductionEuropean Journal of Operational ResearchExpert Systems with Applications
- Partner nations
- PolandItalyUnited Kingdom
In The Last Decade
Miłosz Kadziński
93 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Management Science and Operations Research 1.8k
- Artificial Intelligence 832
- Computational Theory and Mathematics 695
- Control and Systems Engineering 389
- Statistics and Probability 386
Countries citing papers authored by Miłosz Kadziński
This map shows the geographic impact of Miłosz Kadziński's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miłosz Kadziński with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miłosz Kadziński more than expected).
Fields of papers citing papers by Miłosz Kadziński
This network shows the impact of papers produced by Miłosz Kadziński. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miłosz Kadziński. The network helps show where Miłosz Kadziński may publish in the future.
Co-authorship network of co-authors of Miłosz Kadziński
This figure shows the co-authorship network connecting the top 25 collaborators of Miłosz Kadziński. A scholar is included among the top collaborators of Miłosz Kadziński based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miłosz Kadziński. Miłosz Kadziński is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | 2 | |
| 14 | 3 | |
| 15 | 7 | |
| 16 | 27 | |
| 17 | 40 | |
| 18 | 16 | |
| 19 | 22 | |
| 20 | 6 |
About Miłosz Kadziński
Miłosz Kadziński is a scholar working on Management Science and Operations Research, General Energy and Statistics and Probability, having authored 97 papers that have together received 2.9k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (59 papers), Rough Sets and Fuzzy Logic (19 papers) and Advanced Multi-Objective Optimization Algorithms (17 papers). The work is most often cited by research in Management Science and Operations Research (1.8k citations), Statistics and Probability (386 citations) and Computational Theory and Mathematics (695 citations). Miłosz Kadziński has collaborated with scholars based in Poland, Italy and United Kingdom. Frequent co-authors include Roman Słowiński, Salvatore Greco, Tommi Tervonen, Kannan Govindan, Marco Cinelli, R. Sivakumar, Salvatore Corrente, Michael A. Gonzalez, Xiuwu Liao and Vincent Mousseau. Their work appears in journals such as Journal of Cleaner Production, European Journal of Operational Research and Expert Systems with Applications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.